Application of Carbon Fiber and Advanced Composites in Restorative Dentistry: A Study in Material Efficiency, Manufacturing viability, Market Potential and Innovation.

This work presents a multidisciplinary evaluation of Carbon Fibre Reinforced Polyether Ether Ketone (CF-PEEK) as a core material for hybrid dental crowns, combined with lithium disilicate (E-max) veneers. The objective was to assess the mechanical, manufacturing, and economic feasibility of introducing CF-PEEK into restorative dentistry through an engineering-driven approach. A systematic literature review compared the elastic modulus, flexural strength, and density of CF-PEEK with conventional materials such as zirconia and porcelain-fused-to-metal. Results show that CF-PEEK exhibits a modulus close to natural dentin and lower density, offering improved biomechanical compatibility and reduced stress transmission. Additive manufacturing (3D printing) was identified as the most flexible and sustainable production method, minimising material waste and enabling customised crown fabrication. The study concludes that the CF-PEEK + E-max hybrid crown is mechanically viable and aligns with sustainability goals, though improvements in bonding, colour masking, and clinical validation remain necessary. This approach demonstrates how industrial engineering tools including TRIZ, QFD, and KANO can effectively guide innovation in dental materials and workflows

Simulation of Satellite Flares and their Impact on Ground-Based Observations

With a growing number of satellites on Low Earth Orbit (LEO) the problem of light pollution arises, which is caused by the light reflected from satellite modules and directed to the ground-based observatories. This phenomenon is called satellite “flares” or “glints”. The goal of this work is to create a physical simulation model, which can recreate the conditions when the satellite flare is visible. The model is made in Python and uses a simplified geometry of reflection, orbit, solar panel parameters, and real-time TLE data. With the developed model it is possible to evaluate a variety of scenarios: single satellite, constellation and global maps of flare distribution with the given parameters. The simulation model allows for analysing the distribution of flares of time and space and checking the effectiveness of technical and legal norms. In the flow of the work numerical simulations are performed, heat maps are created, analysis and comparison with real data are made. The obtained results demonstrate the potential of this model as an instrument for planning and scheduling observations, developing less bright satellites and creating policy measures to decrease light pollution of the night sky. The results of this thesis are fundamental for expanding the model and integrating real data of all satellites

Development of an Online Presence for Northstar Roleplay

In this thesis, the multiplayer modification RedM and the competitors on it, have been explored in order to establish an online presence that distinguishes Northstar Roleplay from other RedM servers. The project encompasses the development of a clean, visually appealing website designed to present key server features, rules, professions, and the underlying vision, making it the main resource to attract potential new players. Additionally, a comprehensive tutorial video was produced to streamline the onboarding process, offering clear, step-by-step guidance and a personal introduction to the server. An automatic whitelist system was also conceptualized to ensure that new players read and understand the server rules before joining; however, technical challenges prevented its full implementation. Still, the website and video tutorial lay the foundation for the professional online presence of Northstar Roleplay

Analyzing individual chickens' life data to predict egg and growth performance

The 2022 ban on killing male chicks, implemented in Germany and France, tackled ethical problems within egg-laying hen farming. Because of this policy, alternative poultry production methods were created to better meet animal welfare guidelines. To meet this challenge, the University of Bonn launched research into dual-purpose chickens, specifically the British Ixworth breed. Integrating male and female chicken farming offers a new, innovative solution to ethical and sustainability issues in traditional farming by combining egg and meat production. The importance of this research for revolutionizing poultry farming cannot be overstated (Becker et al., 2023). A University of Bonn research team is studying this alternative farming method to determine its productivity and viability. To meet industry needs while prioritizing animal welfare, they evaluate dual-purpose chicken potential by analysing egg (number and weight) and meat (weight) yields. This thesis has four sections, exploring different facets of dual-purpose chickens across four generations via diverse statistical and machine learning methods. First, it examines existing research on various facets of analysing and forecasting individual chicken egg and growth data. It further explores Becker et al.’s 2023 study, “The British Ixworth: individual growth and egg production of a purebred dual-purpose chicken.” Moreover, the linear regression, SVR, KNN, and decision tree models were applied to this data for advanced analysis and prediction. The thesis’s second part details the methodology, including requirements analysis and dataset preparation. This thesis's third section details how data from four generations of chicken life were analysed to predict future egg production and individual chicken growth. Across generations, individual chickens' average body weight and egg weight all showed an increase in the results. Predictions from linear regression and decision tree models show an increase in individual chickens' growth across generations to come. Egg production forecasts were better with the KNN model. This research will use advanced statistical methods and machine learning to model and assess the generational performance of dual-purpose chickens. These tools will forecast future egg and meat production, thus giving key insights to enhance breeding programs. This research aims to optimize dual-purpose chicken production for growth and egg-laying performance. The researchers eagerly anticipate the results, which will help to shape their future poultry farming projects

implementation and investigation of a distributed robotic chess system

This thesis presents and evaluates a distributed robotic system that successfully integrates a native Windows chess engine (Fritz 19) with a containerized ROS2-based robot control system, operating on a single host computer. The architecture is designed to solve the common challenge of bridging disparate operating systems in real-time robotics. Performance analysis over 35 moves demonstrates the architecture’s high reliability, achieving a 100% success rate in the software pipeline from command generation to execution planning. The study quantifies the system’s primary performance bottleneck, showing that the physical robot movement averaged 22.6 seconds, while the underlying communication latency was negligible at 2.89 ms. This highlights a crucial distinction between computational speed and the challenges of physical manipulation. Compared to existing human-robot chess systems, which typically operate within a single OS or rely heavily on computer vision, this work contributes a validated architectural alternative. Its primary contribution is a single-host framework that integrates a native Windows application with a containerized ROS2 system. This provides a robust solution for developers needing to bridge disparate software ecosystems in real-time robotics and establishes a performance baseline demonstrating that such integration is highly efficient

Energy-Efficient Design of Filament Spooling Machines for Sustainable 3D Printing Workflows.

The Thesis encompasses a comprehensive design framework, incorporating detailed calculations for motor selection, tensioning system design, and guide mechanism optimization. The design prioritizes energy efficiency through the implementation of high-efficiency motors, optimized control algorithms, and energy-saving features

Analysis of Health Literacy among Young Adults

This study investigates several key questions related to health literacy, text difficulty, and AI-generated content. Our research explores whether there is a statistical significance in the perceived difficulty of texts based on their authorship (human-translated to layman language, AI-translated, and original excerpts from a medical book), the correlation between participants' evaluations of text difficulty and quantitative analysis of these texts using JASNOPIS, and the relationship between health literacy levels and the ability to recognise AI-generated work. Additionally, the study examines the impact of exposure to AI-made writing on recognising AI-generated content and the relationship between health literacy levels and perceived text difficulty. A cross-sectional survey was conducted with 94 participants, collecting data through online questionnaires between September 19, 2024, and October 9, 2024. Key findings include significant correlations between average perceived difficulty and several JASNOPIS variables. The study also highlights the lack of a significant relationship between exposure to AI-made writing and the ability to recognise AI-generated work. However, the findings indicate that individuals who scored higher on health literacy tests perceived the texts to be easier. The implications of this research emphasise the importance of enhancing health-related and educational materials using plain language principles to improve accessibility and comprehension. Future studies should consider using more objective measures to avoid the influence of personal biases